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   "source": [
    "# Oracle Cloud Infrastructure Generative AI"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Oracle Cloud Infrastructure (OCI) Generative AI is a fully managed service that provides a set of state-of-the-art, customizable large language models (LLMs), that cover a wide range of use cases, and which are available through a single API.\n",
    "Using the OCI Generative AI service you can access ready-to-use pretrained models, or create and host your own fine-tuned custom models based on your own data on dedicated AI clusters. Detailed documentation of the service and API is available __[here](https://docs.oracle.com/en-us/iaas/Content/generative-ai/home.htm)__ and __[here](https://docs.oracle.com/en-us/iaas/api/#/en/generative-ai/20231130/)__.\n",
    "\n",
    "This notebook explains how to use OCI's Genrative AI models with LangChain."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prerequisite\n",
    "We will need to install the oci sdk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install -U oci"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### OCI Generative AI API endpoint \n",
    "https://inference.generativeai.us-chicago-1.oci.oraclecloud.com"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Authentication\n",
    "The authentication methods supported for this langchain integration are:\n",
    "\n",
    "1. API Key\n",
    "2. Session token\n",
    "3. Instance principal\n",
    "4. Resource principal \n",
    "\n",
    "These follows the standard SDK authentication methods detailed __[here](https://docs.oracle.com/en-us/iaas/Content/API/Concepts/sdk_authentication_methods.htm)__.\n",
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Usage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain_community.embeddings import OCIGenAIEmbeddings\n",
    "\n",
    "# use default authN method API-key\n",
    "embeddings = OCIGenAIEmbeddings(\n",
    "    model_id=\"MY_EMBEDDING_MODEL\",\n",
    "    service_endpoint=\"https://inference.generativeai.us-chicago-1.oci.oraclecloud.com\",\n",
    "    compartment_id=\"MY_OCID\",\n",
    ")\n",
    "\n",
    "\n",
    "query = \"This is a query in English.\"\n",
    "response = embeddings.embed_query(query)\n",
    "print(response)\n",
    "\n",
    "documents = [\"This is a sample document\", \"and here is another one\"]\n",
    "response = embeddings.embed_documents(documents)\n",
    "print(response)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Use Session Token to authN\n",
    "embeddings = OCIGenAIEmbeddings(\n",
    "    model_id=\"MY_EMBEDDING_MODEL\",\n",
    "    service_endpoint=\"https://inference.generativeai.us-chicago-1.oci.oraclecloud.com\",\n",
    "    compartment_id=\"MY_OCID\",\n",
    "    auth_type=\"SECURITY_TOKEN\",\n",
    "    auth_profile=\"MY_PROFILE\",  # replace with your profile name\n",
    ")\n",
    "\n",
    "\n",
    "query = \"This is a sample query\"\n",
    "response = embeddings.embed_query(query)\n",
    "print(response)\n",
    "\n",
    "documents = [\"This is a sample document\", \"and here is another one\"]\n",
    "response = embeddings.embed_documents(documents)\n",
    "print(response)"
   ]
  }
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